AI ML Engineering Jobs at Google with Visa Sponsorship
AI ML Engineering jobs at Google span research, product, and infrastructure teams, tackling large-scale models, ML infrastructure, and applied AI systems. The company has a consistent track record of sponsoring work visas for this function, making it a realistic target if you're on H-1B visa, H-1B1 visa, or E-3 visa status.
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Get Access To All JobsMinimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 8 years of experience with one or more general purpose programming languages (e.g., Java, C/C++, or Python).
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of experience with Machine Learning (ML) or quality, working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, and deep model.
- Experience in C++, Dremel/F1, and TensorFlow.
- Experience in Research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
About the job
We are the core team responsible for Search Ads Personalization. Our personalization models and infrastructure permeate through every part of Search Ads - from Ad Retrieval, Ranking, Auction and Creative writing. As a result, our problems are challenging both in depth (understanding nuances of user's needs), and breadth (scale across entire Google Search user base). We work on modeling user preferences and tasks using a myriad of technologies embedding models, language models, as well as building real-time and large scale inference infrastructure.
Personalizing our Ads has proven to be extremely successful, and as a result, it is a key objective of entire Ads organization. Join us to be in the centre of this personalization revolution!
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Responsibilities
- Focus on personalization (P13N) in the Generative AI space (ads on AIM, personalized ads creatives).
- Collaborate across GenAI teams in Ads Quality and GDM to create and execute on a goal/roadmap to ensure that our users feel connected with our GenAI Ads.
- Work on writing ads creatives or ad explanations to account for user tasks and preferences.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 8 years of experience with one or more general purpose programming languages (e.g., Java, C/C++, or Python).
- 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
Preferred qualifications:
- 8 years of experience with data structures and algorithms.
- 6 years of experience with Machine Learning (ML) or quality, working on recommendation systems.
- Experience in recommender systems, clustering algorithms, SQL, and deep model.
- Experience in C++, Dremel/F1, and TensorFlow.
- Experience in Research.
- Ability to drive quality projects end-to-end from design to implementation to eventual launch.
About the job
We are the core team responsible for Search Ads Personalization. Our personalization models and infrastructure permeate through every part of Search Ads - from Ad Retrieval, Ranking, Auction and Creative writing. As a result, our problems are challenging both in depth (understanding nuances of user's needs), and breadth (scale across entire Google Search user base). We work on modeling user preferences and tasks using a myriad of technologies embedding models, language models, as well as building real-time and large scale inference infrastructure.
Personalizing our Ads has proven to be extremely successful, and as a result, it is a key objective of entire Ads organization. Join us to be in the centre of this personalization revolution!
Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Responsibilities
- Focus on personalization (P13N) in the Generative AI space (ads on AIM, personalized ads creatives).
- Collaborate across GenAI teams in Ads Quality and GDM to create and execute on a goal/roadmap to ensure that our users feel connected with our GenAI Ads.
- Work on writing ads creatives or ad explanations to account for user tasks and preferences.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
See all AI ML Engineering Jobs at Google
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineering Jobs at Google.
Get Access To All JobsTips for Finding AI ML Engineering Jobs at Google
Align your portfolio to Google's AI research areas
Google prioritizes ML engineers with experience in large language models, distributed training infrastructure, or ML compilers. Tailor your GitHub, publications, or project work to these domains before applying, since hiring committees assess technical fit against active research priorities.
Target teams that file LCAs year-round
Google's AI and Research org files Labor Condition Applications with DOL continuously, not just during H-1B cap season. Roles under Google DeepMind, Google Research, and core ML infrastructure teams are more likely to have active sponsorship pipelines outside of April.
Use Migrate Mate to filter open roles by visa type
Google posts AI ML Engineering roles across multiple teams simultaneously, and not every opening is tied to a sponsoring team. Use Migrate Mate to filter specifically for roles where H-1B, H-1B1 visa, or E-3 sponsorship is confirmed.
Negotiate offer timing around your OPT or grace period
If your OPT expires before October 1, ask your Google recruiter about cap-gap coverage or a STEM OPT extension. USCIS's cap-gap rule lets you keep working if your H-1B petition is filed before OPT ends, but the timing has to be deliberate.
Prepare for Google's structured technical interview format
Google uses a standardized interview loop for ML roles: coding rounds, ML system design, and a research depth interview. Prepare ML system design answers that reference real production constraints, not just academic benchmarks, since interviewers expect applied scale thinking.
Clarify E-3 or H-1B1 eligibility early with your recruiter
E-3 and H-1B1 visas sit outside the annual H-1B lottery cap and can be processed faster. If you're an Australian or Singapore or Chile national, confirm with Google's immigration team that your target role qualifies as a specialty occupation under the correct visa category.
Frequently Asked Questions
Does Google sponsor H-1B visas for AI ML Engineers?
Yes, Google sponsors H-1B visas for AI ML Engineering roles. Google also sponsors H-1B1 visas for nationals of Singapore and Chile, and E-3 visas for Australian nationals. Sponsorship is handled through Google's internal immigration team in coordination with outside counsel, and the process typically begins after an offer is extended.
Which visa types does Google commonly use for AI ML Engineering roles?
Google sponsors H-1B, H-1B1 visa, and E-3 visas for AI ML Engineering positions. H-1B is subject to the annual lottery cap, with registration in March and an October 1 start date. H-1B1 and E-3 are cap-exempt and can be filed at any point in the year, which makes them faster options for eligible nationals.
What qualifications does Google expect for AI ML Engineering roles?
Google generally expects a bachelor's degree in computer science, electrical engineering, or a related field, with a master's or PhD preferred for research-adjacent roles. Practical experience with ML frameworks like JAX, TensorFlow, or PyTorch is expected. Roles on Google DeepMind or Google Research teams often require demonstrated publication history or equivalent industry research output.
How do I apply for AI ML Engineering jobs at Google?
Applications go through Google's careers portal at careers.google.com. Roles are posted by team, so filtering by function and location matters. If you need visa sponsorship, Migrate Mate lets you browse open AI ML Engineering positions at Google filtered by visa type, so you can focus on roles where sponsorship is confirmed before you apply.
How do I understand the H-1B filing timeline if I get an offer from Google?
If you're subject to the H-1B cap, Google must register you in USCIS's annual lottery, which opens in March. Selection is random, and if chosen, the petition is filed by June for an October 1 start date. If you're already in H-1B status with another employer, Google can file a transfer petition outside cap season with no lottery required.